Senior Engineer, Aspiring AI Builder (Remote, LATAM)

About the role

This role is built for a strong, self-directed software engineer who is passionate about AI/ML and eager to bring it to production.

Responsibilities

• Ship reliable production systems with a focus on ML
• Teach yourself ML concepts and build foundational models
• Deploy and operate ML models on cloud infrastructure
• Build and deploy data pipelines and backend services
• Communicate technical tradeoffs to both technical and non-technical stakeholders

Requirements

• 5+ years of professional software engineering experience
• Strong Python proficiency and ability to write clean, production-grade code
• Demonstrated ability to learn new domains independently
• Hands-on experience with AI/ML, including building and deploying models
• Experience deploying and operating applications on cloud infrastructure
• Experience building data pipelines and backend services at scale
• Strong communication skills, able to explain technical concepts clearly

Qualifications

• Mandatory requirements: 5+ years of professional software engineering experience, strong Python proficiency, ability to teach oneself new domains, hands-on experience with AI/ML, experience deploying and operating applications on cloud infrastructure, experience building data pipelines and backend services at scale, strong communication skills
• Nice-to-have: hands-on experience with major ML frameworks, experience taking ML models into production, familiarity with MLOps tooling, exposure to LLMs, RAG architectures, fine-tuning, or building LLM-powered applications, background in financial services, healthcare, or another regulated industry, contributions to open-source ML projects or public technical work

Benefits

The engagement is fully remote and offers a long-term contract opportunity without an end date.

Pay

Details on pay are not specified at this time.

Schedule

The schedule is not specified at this time.

Skills

• Python programming
• Cloud infrastructure (AWS, GCP, Azure)
• Data pipelines and backend services
• Communication skills
• Major ML frameworks (PyTorch, TensorFlow, etc.)
• MLOps tooling (MLflow, Weights & Biases, Airflow)
• LLMs, RAG architectures, fine-tuning, or building LLM-powered applications
• Background in financial services, healthcare, or another regulated industry
• Contributions to open-source ML projects or public technical work

Benefits

Details on benefits are not specified at this time.

Pay

Details on pay are not specified at this time.

Schedule

The schedule is not specified at this time.